In this study, drought conditions involving risk of fires are detected applying SMOS-derived soil moisture data and land surface temperature models. Moisture-temperature (SM-LST) patterns studied between 2010 and 2014 were linked to main fire regimes in the Iberian Peninsula. Most wildfires burned in warm and dry soils, but the analysis of pre-fire conditions differed among seasons. Absolute values of SM-LST were useful to detect prone- to-fire conditions during summer and early autumn. Complementarily, SM-LST anomalies were related to droughts and high fire activity in October 2011 and February-March 2012. These episodes were coincident with abnormally anticyclonic atmospheric conditions. Results show that combined trends of new soil moisture space-borne data and temperature models could enhance fire risk assessment capabilities. This contribution should be helpful to face the expected increase of wildfire activity derived from climate change.
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Chaparro et al. (2016) studied this question.
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